code: def tsdataset_to_dataloader(
      data, batch_size, lookback, horizon, num_processes
  ):
      if num_processes:  # void the num_processes is none
          if batch_size % num_processes != 0:
              warnings.warn(
                  "'batch_size' cannot be divided with no remainder by "
                  "'self.num_processes'. We got 'batch_size' = {} and "
                  "'self.num_processes' = {}".format(
                      batch_size, num_processes
                  )
              )
          batch_size = max(1, batch_size // num_processes)
      _rolled = data.numpy_x is None
      return data.to_torch_data_loader(
          batch_size=batch_size,
          roll=_rolled,
          lookback=lookback,
          horizon=horizon,
          feature_col=data.roll_feature,
          target_col=data.roll_target,
          shuffle=True,
      )
  
imports: import torch
  import torch.nn
  import warnings
  import random
  import numpy
  from torch.utils.data import TensorDataset, DataLoader
  import numpy
  import multiprocessing
  import warnings
  import math
label_desc: Use image node_id 10 for calling a global function with example usage: tsdataset_to_dataloader(data, batch_size, lookback, horizon, num_processes) and returns: data